Consolidated-Drained Triaxial Compression Testing of Peat
Bibliographic record
Abstract
Abstract Recent peat soil problems, including failures of dykes, foundations, and slopes in peat deposits, have focused greater attention on understanding the mechanical behavior of peat. Stability calculations routinely involve effective stress analysis, with pertinent strength and stiffness parameters often determined from standard triaxial testing, without special consideration given to internal tensile reinforcement provided by the fiber content and the high compressibility of the peat material. This paper investigates consolidated-drained triaxial compression testing applied to peat soils. Significant differences in mini-structure and fiber content among test specimens of undisturbed, reconstituted, and blended peat materials were found not to cause significant differences in shear resistance under drained triaxial compression, with mobilized shear resistance increasing approximately linearly with increasing axial strain. Hence it was concluded that c′ and φ′ deduced from drained triaxial compression testing of peat are unlikely to be intrinsic material properties, and rather are largely a function of strain level, with higher values of φ′ deduced for higher strain levels. The end of primary consolidation should be deduced from pore-water pressure measurements rather than the volume change response, although the repeatability of the triaxial consolidation tests was generally found to be poor on account of the natural variability of peat and the small size of the test specimens.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".